# DeepInfra vs Muse Spark Open

> DeepInfra scores 63 (B) to Muse Spark Open's 53.4 (D) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.

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- Updated: 2026-10-15

DeepInfra scores 63 (B) on agent readiness against Muse Spark Open's 53.4 (D), and leads in 6 of 7 scored categories. Muse Spark Open leads on payments & pricing. Both do llm inference.

- DeepInfra: grade B, 63/100, rank #442 of 1095. Markdown https://www.anchorterminal.com/tools/deepinfra.md · JSON https://www.anchorterminal.com/api/v1/tools/deepinfra.json
- Muse Spark Open: grade D, 53.4/100, rank #760 of 1095. Markdown https://www.anchorterminal.com/tools/muse-spark-open.md · JSON https://www.anchorterminal.com/api/v1/tools/muse-spark-open.json
- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md
- All 210 models comparisons: https://www.anchorterminal.com/compare/inference/index.md

## Which one, for what

### DeepInfra (B)

Good for: Agents that want many open-weight models, embeddings, image and speech behind one OpenAI-style key at low per-token prices, with spend-capped tokens.

Ahead on:
- Reliability, 70 against 42
- Schema & documentation, 69 against 61
- Agent ergonomics, 77 against 69
- Security & auth, 64 against 44
- Maintenance & community, 65 against 60
- Transparency & trust, 67 against 53

Also in its favour:
- A hosted endpoint, with nothing to install

Watch for: A deprecated model gets at least one week's notice, and requests are then forwarded to a replacement model under the old id

### Muse Spark Open (D)

Good for: A team with a four-GPU Blackwell node, or two to four Mac Studios, that wants a 1M-token multimodal coding and agent model on its own hardware with no prompts leaving it.

Ahead on:
- Payments & pricing, 50 against 20

Also in its favour:
- No key needed to call it

Watch for: The NVFP4 checkpoint (about 537 GB) serves on four B300 GPUs and the BF16 one (about 1.65 TB) on eight


## Score by category

| Category | Weight | DeepInfra | Muse Spark Open | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 70 | 42 | DeepInfra +28 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 69 | 61 | DeepInfra +8 |
| Agent ergonomics | 13% (16.2 this run) | 77 | 69 | DeepInfra +8 |
| Security & auth | 14% (17.5 this run) | 64 | 44 | DeepInfra +20 |
| Payments & pricing | 10% (12.5 this run) | 20 | 50 | Muse Spark Open +30 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 65 | 60 | DeepInfra +5 |
| Transparency & trust | 7% (8.8 this run) | 67 | 53 | DeepInfra +14 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **63 · B** | **53.4 · D** | |

## Facts side by side

| Fact | DeepInfra | Muse Spark Open |
| --- | --- | --- |
| Kind | Model API | Model API |
| Vendor | Deep Infra Inc. | Meta |
| Hosted endpoint | `https://api.deepinfra.com/v1/openai` | no (local only) |
| Transports | HTTP | HTTP |
| Auth | API key | None |
| Pricing | Pay per use | Free |
| x402 | no | no |
| Licence | Proprietary service under the DeepInfra Terms of Service. The Python and Node SDKs and the docs repository are MIT | Muse Model Licence (source-available weights, not an OSI licence), free of charge with an attribution notice, a separate agreement with Meta before Model as a Service by a licensee group above $20M gross revenue, and the Muse Spark Open Usage Policy |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| Last release | 2026-10-07 | 2026-10-15 |
| Terms last updated | 2026-08-17 |  |
| Privacy policy last updated | 2026-08-15 | no document linked |
| Customer content may train models | not found in the text |  |
| Terms restrict automated access | not found in the text |  |
| Terms restrict benchmarking | yes |  |
| Terms or service can change without notice | not found in the text |  |
| Arbitration or class-action waiver | yes |  |
| Popularity | 21 stars, 1.2k npm/wk, 50 PyPI/wk | none |

## Verdicts

**DeepInfra.** The model list, context sizes and per-token prices are readable without a key, and keys can carry an IP allowlist, a monthly spending cap and model-limited JWTs. Deprecated models get one week's notice and are then redirected to another model, there is no changelog or SLA, and an account needs a card or prepayment before any call.

**Muse Spark Open.** Muse Spark Open runs on the owner's hardware in seven runtimes, with OpenAI-compatible servers in vLLM and SGLang, standard tool calls, a 1M-token context and Meta's own serving docs. Serving the 537 GB NVFP4 checkpoint takes four B300 GPUs, Meta's download is gated by manual review, and the licence adds attribution and a revenue threshold for model resellers.

## Before you call either

### DeepInfra

1. Call `GET https://api.deepinfra.com/v1/openai/models` at start-up for ids, context sizes and prices. No key is needed
2. Check the `model` field of each response. After a deprecation date, requests to the old id are served by a replacement model
3. Ask the account owner for a scoped JWT limited to the models and spend the task needs, not the full API key
4. Stay under 200 concurrent requests per model. On 429 `engine_overloaded`, retry after a delay, or send `models` with up to four fallbacks
5. Never inspect a JWT with `GET /v1/scoped-jwt?jwtoken=`, which puts the token in the URL. Keep credentials in the `Authorization` header

### Muse Spark Open

1. Start vLLM or SGLang with `--reasoning-parser muse --tool-call-parser muse` (vLLM also `--enable-auto-tool-choice`), or tool calls come back as raw text
2. Set `reasoning_effort` to `low` or `medium` for short tasks. The default is `xhigh`, reasoning can't be turned off, and other values return an error
3. Stop only on `<|eot|>` and end of text. Stopping on `<|eom|>` cuts off tool calls and final answers
4. Stream long generations and leave `max_tokens` room for reasoning, or `content` can come back empty with `finish_reason` `length`
5. Don't call Meta Model API for this model. Use a self-hosted server or a hosted provider's model string, such as `meta-models/muse-spark-open`

## Questions

### Which is better for AI agents, DeepInfra or Muse Spark Open?

DeepInfra scores 63 (B) on agent readiness against Muse Spark Open's 53.4 (D), and leads in 6 of 7 scored categories. Muse Spark Open leads on payments & pricing.

### Do DeepInfra and Muse Spark Open need an API key?

DeepInfra needs an API key. Muse Spark Open needs no key.

### Can an agent call DeepInfra and Muse Spark Open without installing anything?

DeepInfra has a hosted endpoint at https://api.deepinfra.com/v1/openai. No hosted endpoint is listed for Muse Spark Open.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/deepinfra-vs-muse-spark-open.json, and with the fewest tokens: https://www.anchorterminal.com/compare/deepinfra-vs-muse-spark-open.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "deepinfra", "b": "muse-spark-open"}`. From a terminal: `anchor compare deepinfra muse-spark-open`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/deepinfra.json and https://www.anchorterminal.com/api/v1/tools/muse-spark-open.json

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